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UAL Research Online

Ambient intelligence in self-organising assembly systems using the chemical reaction model

Frei, Regina and Serugendo, Giovanna Di Marzo and Serbanuta, Traian Florin (2010) Ambient intelligence in self-organising assembly systems using the chemical reaction model. Journal of Ambient Intelligence and Humanized Computing, 1. pp. 163-184. ISSN 1868-5137

Type of Research: Article
Creators: Frei, Regina and Serugendo, Giovanna Di Marzo and Serbanuta, Traian Florin
Description:

This article discusses self-organising assembly systems (SOAS), a type of assembly systems that (1) participate in their own design by spontaneously organising themselves in response to the arrival of a product order and (2) manage themselves during production. SOAS address the industry's need for agile manufacturing systems to be highly responsive to market dynamics. Manufacturing systems need to be easily and rapidly changeable, but system re-engineering/reconfiguration and especially their (re-) programming are manual, work-intensive and error-prone procedures. With SOAS, we try to facilitate this by giving the systems gradually more self-* capabilities. SOAS eases the work of the SOAS designer and engineer when designing such as system for a specific product, and supports the work of the SOAS operator when supervising the system during production. SOAS represent an application domain of ambient intelligence and humanised computing which is not frequently considered, but therefore none the less important. This article explains how an SOAS produces its own design as the result of a self-organising process following the Chemical Abstract Machine (CHAM) paradigm: industrial robots self-assemble according to specific chemical rules in response to a product order. This paper reports on SOAS in general, the specification of the chemical reactions and their simulation in Maude.

Official Website: https://link.springer.com/article/10.1007/s12652-010-0016-0
Publisher/Broadcaster/Company: Springer Nature
Your affiliations with UAL: Colleges > London College of Fashion
Date: 16 June 2010
Digital Object Identifier: 10.1007/s12652-010-0016-0
Date Deposited: 26 Jul 2024 16:13
Last Modified: 26 Jul 2024 16:13
Item ID: 22326
URI: https://ualresearchonline.arts.ac.uk/id/eprint/22326

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